Fuzzy technology is adaptive and easily applicable in different areas.Fuzzy logic provides powerful tools to capture the perception of natural phenomena. The paper deals with tuning of neuro-fuzzy controllers for integrating plant and for integrating plants with time delay. The designed approach is verified on three examples by simulations and compared plants with classical PID control. Designe...

This paper deals with the modelling and control of semi-batch reactor used for chromium sludge regeneration process. A comparison of three process control approaches is presented. Usual PID controller without online identification (OI) and adaptive PID controller were adapted to semi-batch rector process in our previous studies. In this study the two-degrees-of-freedom (2DOF) controller is deve...

A novel tuning method is proposed for the design of fuzzy PID controllers for multivariable systems. In the proposed method, a PID controller is expressed in terms of fuzzy rules, in which the input variables are the error signals and their derivatives, while the output variables are the PID gains. In this manner, the PID gains are adaptive and the fuzzy PID controller has more flexibility and ...

This paper presents a PID tuning method for unstable processes using an adaptive-network-based-fuzzy-inference system (ANFIS) for given gain and phase margin (GPM) speci)cations. PID tuning methods are widely used to control stable processes. However, PID controller for unstable processes is less common. In this paper, the PID controller parameters can be determined by the ANFIS. Because the de...

This paper presents the design of an indirect adaptive feedback linearization (FBL)based control using dynamic neural networks (DNN) for full-car nonlinear electrohydraulic suspensions. Particle swarm optimization (PSO) algorithm is used in training the DNN to learn the dynamics of the system. A multi-loop, PSO-optimized proportional-integral-derivative (PID) control is implemented for the feed...

Abstract:––Accurate controlling of Rudder is a challenging issue, it demands co design approach. Researchers are trying to provide solutions by upgrading hardware functionalities and by reducing the computational complexity of algorithm. PID, Adaptive and Predictive algorithms are the most widely used algorithm for Rudder control. This paper discusses simple, cost effective, PID based, 8051 mic...

An adaptive version of growing and pruning RBF neural network has been used to predict the system output and implement Linear Model-Based Predictive Controller (LMPC) and Non-linear Model-based Predictive Controller (NMPC) strategies. A radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.An Unscented Kal...

This paper presents the development of a Genetic Algorithm Supervisory Loop (GASL) to enhance the performance of Adaptive Controllers in the Self Tuning Regulator (STR) framework. The GASL is designed to tune the identification model and control parameters to achieve an optimum performance of the process. The STR controller used to demonstrate the technique effectiveness is a real time Proporti...

A class of adaptive disturbance tracking controllers (ADTCs) is augmented with disturbance and state estimation and adaptive state feedback, in which a controller and estimator, which are designed on the basis of a lower-order model, are used to control a higher-order nonlinear plant. The ADTC requires that the plant be almost strict positive real (ASPR) to ensure stability. In this paper, we s...

As traditional PID controller has mature technique, it is applied widely. But the design of it depends on mathematical model of the controlled object. But the parameters of PID controller use engineering tuning method, it requires much time and effort and the parameters are only effect in a specific range. It is not suitable for complicated nonlinear and time-variable system. In recent year, pe...